Anesthesia information management systems (AIMS) have evolved from simple, automated intraoperative record keepers in a select few institutions to widely adopted, sophisticated hardware and software solutions that are integrated into a hospital’s electronic health record system and used to manage and document a patient’s entire perioperative experience. AIMS implementations have resulted in numerous billing, research, and clinical benefits, yet there remain challenges and areas of potential improvement to AIMS utilization. This article provides an overview of the history of AIMS, the components and features of AIMS, and the benefits and challenges associated with implementing and using AIMS. As AIMS continue to proliferate and data are increasingly shared across multi-institutional collaborations, visual analytics and advanced analytics techniques such as machine learning may be applied to AIMS data to reap even more benefits.
From the *Department of Anesthesiology and Critical Care, Division of General Anesthesia, Perelman School of Medicine at the University of Pennsylvania and The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; and †Department of Anesthesiology, Johns Hopkins All Children’s Hospital and Johns Hopkins University School of Medicine, Baltimore, Maryland.
Accepted for publication September 8, 2017.
The authors declare no conflicts of interest.
Reprints will not be available from the authors.
Address correspondence to Allan F. Simpao, MD, MBI, Department of Anesthesiology and Critical Care, Division of General Anesthesia, Perelman School of Medicine at the University of Pennsylvania and The Children’s Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104. Address e-mail to firstname.lastname@example.org.